code: def _load_meta_algorithm(
      self, root_path: str, node_metadata: Dict[str, Any]
  ) -> None:
      stages = []
      for stage_meta in node_metadata["stages"]:
          stage = ParamsReadWrite._load_instance_from_metadata(
              stage_meta, root_path
          )
          stages.append(stage)
  
      if isinstance(self, Pipeline):
          self.setStages(stages)
      elif isinstance(self, PipelineModel):
          self.stages = stages
      else:
          raise ValueError()
  
imports: from typing import Any, Dict, List, Optional, Union, cast, TYPE_CHECKING
  import pandas
  from pyspark import keyword_only, since
  from pyspark.ml.connect.base import Estimator, Model, Transformer
  from pyspark.ml.connect.io_utils import ParamsReadWrite, MetaAlgorithmReadWrite
  from pyspark.ml.param import Param, Params
  from pyspark.ml.common import inherit_doc
  from pyspark.sql.dataframe import DataFrame
label_desc: Use image node_id 4 for calling the _PipelineReadWrite obj's underlying member method code with example usage: obj._load_meta_algorithm(root_path, node_metadata) without return types